Adaptive Variable Clustering in Gaussian Graphical Models. - Siqi Sun; Yuancheng Zhu; Jinbo Xu (AISTATS, 2014)

Quantized Estimation of Gaussian Sequence Models in Euclidean Balls. - Yuancheng Zhu; John D. Lafferty (NIPS, 2014)

The Log-Shift Penalty for Adaptive Estimation of Multiple Gaussian Graphical Models. - Yuancheng Zhu; Rina Foygel Barber (AISTATS, 2015)

Nonparametric Estimation of Scale-Free Graphical Models. - Yuancheng Zhu; Zhe Liu; Siqi Sun (CoRR, 2015)

Local Minimax Complexity of Stochastic Convex Optimization. - Sabyasachi Chatterjee; John C. Duchi; John D. Lafferty; Yuancheng Zhu (NIPS, 2016)

Learning Nonparametric Forest Graphical Models with Prior Information. - Yuancheng Zhu; Zhe Liu; Siqi Sun (AISTATS, 2017)

Distributed Nonparametric Regression under Communication Constraints. - Yuancheng Zhu; John Lafferty (ICML, 2018)

Statistical Inference for Online Learning and Stochastic Approximation via Hierarchical Incremental Gradient Descent. - Weijie Su; Yuancheng Zhu (CoRR, 2018)

Improved Random Forest Algorithm Based on Attribute Comprehensive Weighting Used in Identification of Missing Data in Power Grid. - Yihe Wang; Yufei Jin; Yuancheng Zhu; Xiyuan Li; Dazhi Li (ICBDS, 2020)

HiGrad: Uncertainty Quantification for Online Learning and Stochastic Approximation. - Weijie J. Su; Yuancheng Zhu (J. Mach. Learn. Res., 2023)